This data set provides daily sea ice motion vectors derived from a wide variety of sensors in both gridded and non-gridded (raw) files. For the gridded data, weekly and monthly mean fields are also provided for the entire time series—from November 1978 through May 2015. Browse images of these mean fields are also available.

Detailed Data Description

Format

Daily Gridded and Mean Gridded Files

The daily gridded files provide ice motion vectors by merging the raw ice motion vectors together using a set of rules. See the Processing Steps section of this document for more information on this merging process.

The mean gridded files provid averages of the daily gridded data at different resolutions: weeks and months and the complete time series. Both the daily and mean gridded fields are projected to Northern and Southern Hemisphere EASE-Grids. Data are stored in 2-byte integer binary format (little endian) and are pixel-interleaved three-item vectors (u, v, 3). Each vector represents three variables:

U Component (cm/sec)—Scaled by a factor of 10; divide by 10 to revert to original units.

V Component (cm/sec)—Scaled by a factor of 10; divide by 10 to revert to original units.

Third Variable—Varies for daily and mean grids (see below). For both daily and mean grids, a pixel value of 0 in the third variable indicates no vectors at that location.

Third Variable for Daily Grids

For the daily grids, the third variable contains the square root of the estimated error variance, scaled by a factor of 10, at a given location. The error variance is the estimated error of that vector obtained from the optimal interpolation process. The input vectors from the individual sources (NCEP/NCAR Winds, SSM/I, SSMIS, SMMR, AMSR-E, and AVHRR) are weighted separately based upon cross-correlations with buoy vectors. The optimal interpolation uses these weights, along with their distances from the location being estimated, to obtain the final error variance.

If the closest input vector was greater than 1250 km, then a value of 1000 is added to this variable. Because interpolation was applied to a surface map from passive microwave data, coastlines may contain false ice. In this case, the third variable was assigned a negative value to allow users to remove these vectors near coastlines (within 25 km). For example, a value of -1035 indicates all of the following conditions:

The vector was near a coastline

The nearest sampled vector was further than 1250 km

The vector had a σ value of 3.5, or the estimated error variance (σ2) is 12.25

Third Variable for Mean Grids

For the mean grids, the third variable is the number of daily gridded values that contributed to the mean value. For example, at a grid point in the weekly product, the number of vectors would be between 1 and 7, indicating the number of days of the week with a valid vector at that grid point; for a monthly product, the number would be between 1 and 31. Generally, the greater fraction of days in the mean field that contain valid values, the higher the data quality.

Thus, the information contained in the third variable provides a means of characterizing data quality, in addition to the "near coastline" check described above. For example, a data user might choose to filter out vectors with error variances above a certain level or values for which the nearest observed vector was beyond a particular distance.

Raw Ice Motion Vector Files

The raw ice motion vector files provide the motion vectors from each specific sensor in space-delimited ASCII text format. Each daily file contains a variable number of vectors that are described at the top of every file in a one-line header containing three numbers as described in Table 1.

Table 1. Header Row Description for Raw Ice Motion Vector Files

Number

Description

First

Specifies the number of vectors (lines) in the file

Second

Original grid dimensions (x)

Third

Original grid dimensions (y)

After the header line, the data are listed in five columns for all files, except for the IABP buoy data which contains six columns. The columns are described in Table 2.

Table 2. Column Descriptions for Raw Ice Motion Vector Files

Column

Name

Description

1

x

EASE-Grid row number for the start of the vector (vector starts in the center of the grid cell). The upper left corner is represented by x = -0.5

2

y

EASE-Grid column number for the start of the vector (vector starts in the center of the grid cell). The upper left corner is represented by y = -0.5

3

u

The horizontal vector component in cm/sec

4

v

The vertical vector component in cm/sec

51

z

Source of the data; z value varies depending on instrument:

AMSR-E:

z = 0.0 – 1.0 (correlation coefficient); only 89V GHz channel used.

AVHRR:

z = Number of vectors averaged together at a given location from up to four passes and two channels (thermal and visible).

Buoys:

z = IABP buoy number

SMMR:

z = 1: The vector was from 37V GHz channel
z = 2: The vector was from both 37 GHz channels

SSM/I and SSMIS:

z = 1: The vector was from 37V GHz channel
z = 2: The vector was from both 37 GHz channels
z = 3: The vector was derived from the 85V GHz channel

Winds:

z = 1: From NCEP/NCAR wind data

1 For the buoy data, there are six columns with the fifth column containing time of day in Universal Coordinated Time (UTC) and the sixth column containing the z value with the IABP buoy number.

Refer to Table 4 for the valid values for the file name variables listed above.

Table 4. Ice Motion File Naming Convention

Variable

Description

icemotion.vect

Indicates that the file contains ice motion vectors

xxxx

Sensor File (amsre1, avhrr,buoy1, ssmi, or smmr2) wind

yyyy

4-digit year3

ddd

3-digit day of year3

h

Hemisphere (n: Northern, s: Southern)

vVV

Version (v3)

.ext

File extension (.txt: ASCII text file)

1 Available for Northern Hemisphere only. 2 Files named ssmi include two sensors: SSM/I and SSMIS.3 File dates indicate the beginning of the vector, either the start of buoy motion or the first satellite image.

Mean Gridded Data Files

This section explains the mean gridded data file naming convention used for this product with an example.

Tables 7 and 8 list the values of corner grid cells for the Northern and Southern Hemispheres, respectively.

Table 7. Northern Hemisphere Pixels

Corner

Center of Pixel

Outer Edge of Pixel

Upper Left

29.89694° N, 135.00000° W

29.71270° N, 135.00000° W

Upper Right

29.89694° N, 135.00000° E

29.71270° N, 135.00000° E

Lower Left

29.89694° N, 45.00000° W

29.71270° N, 45.00000° W

Lower Right

29.89694° N, 45.00000° E

29.71270° N, 45.00000° E

Table 8. Southern Hemisphere Pixels

Corner

Center of Pixel

Outer Edge of Pixel

Upper Left

37.13584° S, 45.00000° W

36.95776° S, 45.00000° W

Upper Right

37.13584° S, 45.00000° E

36.95776° S, 45.00000° E

Lower Left

37.13584° S, 135.00000° W

36.95776° S, 135.00000° W

Lower Right

37.13584° S, 135.00000° E

36.95776° S, 135.00000° E

Spatial Coverage Maps

Figure 1a. Spatial Coverage Map for the Northern Hemisphere

Figure 1b. Spatial Coverage Map for the Southern Hemisphere

Determining Vector Components

Note that the U and V vector components are determined with respect to the grid; positive U vectors run from left to right and positive V vectors run from bottom to top. Thus, consider the longitude when retrieving East/West and North/South components.

Spatial Resolution

Projection and Grid Description

Data are georeferenced to the EASE-Grid projection, an azimuthal equal area projection. The northern grid is 361 x 361, centered on the geographic North Pole. The southern grid is 321 x 321, centered on the geographic South Pole. Nominal grid size is 25 km. Grid coordinates begin in the center of the upper left grid cell. These grids are subsets of the Northern and Southern EASE-Grids.

Buoy Data Removed

In Version 3, buoy ice motion estimates greater than 70 cm/s over a 24 hour period were deemed to be physically unrealistic; thus, buoy velocities that exceed this threshold were excluded from this data set.

Ice Motion Missing Data

In Version 3, there are some missing days of data in the Southern Hemisphere because there was not enough data from SSMI or AVHRR to yield ice motion vectors. There are a total of 13164 days of data. We have 12992 days of that data, with 172 days of missing data. Refer to Table 10 for the days of the missing data.

Table 10. Days of Missing Ice Motion Data

Year

Missing Days of Data

1979

12, 13, 20-25, 28, 29, 48, 49, 60, 61 354, 355, 364

1980

1, 2 11-16, 19-22, 25-28, 31-36, 39-46, 67, 68, 73-78, 87, 88

1981

15 16 23 24 27 28 31 32 39 40 51 52 61 62 69 70

1982

28-32, 36, 54-57, 215-217

1983

27 28 44 57

1984

1 14 15 18 26 27 38 39 80 81 82 235 236 237

1985

15 36 37

1986

87 89 337 350

1987

18 19 24 25 26 27 357 360 361 362

1988

37 59 60

1989

22 23 48 66 72 73 137 139 361 362 364

1990

18 33 35 42 46 48 49 51 53 68 78 93

1991

53 68 75

1992

7 15 25 38 44

1993

69

1994

323 324 325

1996

335 336

1997

29 34

2000

36

2004

6

2005

33

2010

30 32 33 178 179

2011

20

AVHRR Data Removed

It was discovered that previous versions of AVHRR motion vector data files had motion estimates based on comparison of AVHRR images that were misregistered relative to each other. Thus, some AVHRR motion estimates were removed from Version 3 data. Refer to Table 11 for the dates of the data that were removed.

Table 11. Days of Missing AVHRR Data

Hemisphere

Year

Missing Days of Data

Northern

1993

258

1996

225 226

Southern

1981

355

1983

174, 206-208, 241-242, 262-270, 306, 329, 343

1984

332 333

1985

97

1987

250

1988

121

1989

50

1994

16

1995

7 18

1996

137 138

2000

72 282

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Sample Data Record

Following is a sample of raw vectors derived from SSM/I data. The first ten lines of icemotion_vect_ssmi_2003078_n_v3.txt are shown in Figure 2. The first line is the header and indicates that this file contains 1267 vectors and that the original grid was 1805 x 1805 pixels. For a description of the data columns, see the Raw Ice Motion Vectors Format section of this document. Figure 3 shows a browse image for the monthly mean ice motion for January 2014.

Software and Tools

ImageJ is a visualization tool used to examine raw binary data files. While ImageJ can handle multiple images in a single data file, these images must be sequential rather than interleaved. The binary gridded ice motion files may be converted from interleaved to sequential files using the C program uninterleave.c available via the FTP directory in the tools folder. Further instructions on running uninterleave and using ImageJ can be found in the README.sequential file in the FTP directory.

A Read/Plot Data IDL program is available via the FTP directory in the tools folder that can read ice motion data and create PostScript plots or display data to a screen.The file show_vectors_v3.prodisplays AMSR-E, AVHRR, SMMR, SSM/I, SSMIS, and buoy-derived ASCII sea ice motion vectors. The map filesnsidc_north_map and nsidc_south_mapmust be in the same directory as the IDL program.

The following is an example of running an IDL program using the vector file for SSM/I and SSMIS:IDL> show_vectors_v3, 'icemotion_vect_ssmi_2012365'

An Animate Data IDL program is available via the FTP directory in the tools folder that animates raw data and daily and mean gridded data by day, week, month, or year. The file disp_ice_motion_v3.pro displays ice motion vectors. The map files nsidc_north_map and nsidc_south_map must be in the same directory as the IDL program.

To run this code, open IDL and type the name of the routine. For example:

In addition, the tools directory contains the following latitude and longitude grids with 25 km pixel spacing, which provide row/column to latitude/longitude conversion information: north_x_y_lat_lonsouth_x_y_lat_lon

Table 13 provides the descriptions for the four columns in each of these files.

Table 13. Column Descriptions for Latitude and Longitude Files

Column

Name

Description

1

x

Grid row number

2

y

Grid column number

3

lat

Corresponding latitude

4

lon

Corresponding longitude

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Data Acquisition and Processing

Theory of Measurements

Sea ice movement is measured using imagery acquired by frequent, repeat coverage of remote sensing instruments. Ice motion computed from satellite imagery represents the displacement between the acquisition times of two images with the same spatial coverage. Researchers identify a feature, such as an ice floe, on two registered images and measure its pixel displacement. Ice velocity vectors are computed based on the pixel resolution and time span between images.

A more automated method is to measure the correlation of groups of pixels between image pairs. A small target area in one image is correlated with several areas of the same size in a search region of the second image. The displacement of the ice is then defined by the location in the second image where the correlation coefficient is the highest. This spatial correlation method is used to produce ice motion vectors for this data set. This approach is generally valid over short distances away from the ice edge in areas where ice conditions are relatively stable from day to day. Spatial correlation methods cannot, however, find matches between images where a complete knowledge of ice dynamics is needed; for example, in areas where ice is deforming or in the ice margins near the open ocean where the spatial or spectral characteristics of the ice within a pixel are changing rapidly (Emery, Fowler, and Maslanik 1995).

Ice Motion Estimates Where No Ice Exists

The passive microwave ice motion estimates are based on changes in brightness temperatures over consecutive days. We used ice concentration estimates greater than 15 percent from the Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data Set, NSIDC-0051, to indicate where ice extent is present.

The methods used to generate these ice motions at current resolutions requre fairly large areas of ocean. For instance, no motions can be calculated in the Canadian Archipelago. The absence of ice motion estimates in such locations does not imply the absence of ice in these locations.

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Data Sources

AVHRR Data

AVHRR Global Area Coverage (GAC) images at a 5 km gridded resolution were used to estimate ice motion over the Arctic and Antarctic for several reasons. First, they were available for nearly two decades. Second, they provide an intermediate spatial resolution between passive microwave and buoys and finer time sampling than microwave data. Finally, they are not subject to the same error sources as the other data sets. AVHRR channel 2 (visible band) and channel 4 (infrared) are used.

Buoy Data

International Arctic Buoy Program (IABP) C buoy position data were used to calculate ice motion vectors from buoys. IABP provides buoy location information through satellite tracking of buoys placed on sea ice. Several buoy locations are determined each day and corresponding ice motions are calculated. Ice motion from buoys is very accurate, but it is limited since the numbers and locations of buoys are driven by cost and logistics. In addition, buoys have not been placed on ice in the Eastern Arctic.

IABP buoy locations are generally provided every 12 hours: at noon and at midnight Greenwich time. This ice motion product uses 24-hour motion estimates from the IABP. For example, the IABP motion estimate for a buoy at noon on 01 January 2010 is derived by taking the difference of the buoy's location at noon on 02 January 2010 and its location at noon on 01 January 2010 and then dividing by 24 hours. The intervening midnight location value is not factored into the noon-to-noon 24-hour motion estimate. Similarly, the IABP motion estimate for midnight is calculated the same way, ignoring the intervening noon location information. Therefore, each buoy generally has two independent 24-hour motion estimates, one for midnight and one for noon.

NCEP/NCAR Data

NCEP/NCAR Reanalysis data were used to derive wind vectors for this data set. The data, called U-wind at 10 m, are available from the NOAA Earth System Research Laboratory (ESRL) Physical Sciences Division (PSD).

The NCEP/NCAR Reanalysis source data set is an assimilation of land surface, rawinsonde, ship, pibal, aircraft, satellite, and various other data within a global weather model. A partial list of some of the sensors and data sources used in the NCEP/NCAR Reanalysis is provided in Table 14. For complete documentation regarding the sensors used as a basis for the NCEP/NCAR data, refer to the NCEP-NCAR 50-Year Reanalysis: Monthly Means CD-ROM and Documentation paper (Kistler 2001).

The TOVS suite of sensors provides global measurements used in weather forecasting, such as the vertical distribution of temperature and moisture in the atmosphere.

Surface Wind Speed Data

Special Sensor Microwave Imager (SSM/I)

SSM/I data were used with the Krasnopolsky et al. (1995) algorithm which resulted in wind speeds closer to buoy data, and coverage under cloudy conditions. Measurements include SSM/I wind speed, total precipitable water, and other parameters. (Kalnay et al. 1996)

Satellite Cloud Drift Wind Data

Geostationary Meteorological Satellite (GMS) data

The GMS program is a series of satellites operated by the Japan Meteorological Agency (JMA). The Visible and Infrared Spin Scan Radiometer (VISSR), the primary instrument aboard GMS, collects visible and infrared images of Earth and its cloud cover.

Merge the Ice Motion Fields​Each of the ice motion estimates, for example from NCEP winds, IABP buoys, or AMSR-E, are computed and gridded individually. Once computed, these independent estimates are then combined into a final motion estimate. Each source is weighted according to the expected accuracy of the source data. For example, estimates derived from nearby buoys are weighted higher than NCEP-derived estimates.

To compute the final gridded motion estimate, each of the independent estimates are mapped to the output grid. A source-weighted and distance-weighted average of the nearest 15 estimates is used to compute the final motion estimate. Note that where data are sparse, the data sources will be widely separated; and when data are dense, only the very nearest estimates are considered. If the motion estimates vary significantly from each other, this method can result in motion fields that do not always vary smoothly.

For the weekly means, at least five out of seven days were needed to compute each vector mean. Weekly means for each year start at 01 January for consistency. The last day of each year (or last two days if in a leap year) were not used. For example, week 1 is always 1-7 January and week 52 is either 24-30 December or 23-29 December, if in a leap year.

For the monthly means, at least 20 days were needed. For any mean greater than one month, at least 40 days were needed.

Write Data to ASCII and Binary Data Files

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Processing History

Table 16 outlines the processing and algorithm history for this product.

DOCUMENT REVISION DATE

How To

This article describes the actions to perform in order work with NSIDC-0116 in ArcGIS. At the time of writing, this tutorial is relevant for ArcMap10.5 and earlier. The following steps will show you how to prepare the binary files for import, format conversion, geolocation/projection, and display... read more